Software Engineer III, AI/ML Machine Learning, Core
Job Description
- Master's/PhD in Computer Science
- Experience with large-scale infrastructure
- Experience developing accessible technologies
- Experience with version control and software development tools
- Bachelor's degree or equivalent experience
- 2+ years software development experience
- 2+ years experience with data structures/algorithms
- AI/ML model development & deployment
- Strong programming skills (Python, Java, C++)
- Collaboration with cross-functional teams
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 2 years of experience with data structures or algorithms in either an academic or industry setting.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
- Experience developing accessible technologies.
- Proficiency in one or more programming languages commonly used in software development, such as Python, Java, or C++. Experience with version control systems (e.g., Git) and software development tools (e.g., IDEs, CI/CD pipelines) is highly desirable.
- Strong hands-on experience in developing and deploying AI/ML models and algorithms.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
Responsibilities
- Develop AI/ML Solutions: Experiment, fine tune, and deploy AI/ML models and develop AI/ML applications that optimize developer productivity, streamline development workflows, and automate repetitive tasks. This may include test code generation, debugging assistance, and other productivity-enhancing tools.
- Documentation and Communication: Prepare comprehensive technical documentation, including model architectures, algorithms, and implementation details. Present findings, results, and recommendations to both technical and non-technical stakeholders in a clear and concise manner.
- Model Training and Evaluation: Collect and preprocess data, build and train AI/ML models using various algorithms and techniques, and evaluate their performance.
- Collaboration: Work closely with cross-functional teams, including software developers, data scientists, product managers, and UX designers, to understand their needs and pain points. Collaborate effectively to define and implement AI/ML solutions that address these challenges and improve overall developer productivity.
